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Why Analytics Platforms are Failing Your Data Scientists

The research firm Market Research Future recently predicted the market for global data analytics will grow by 30 percent through 2023 to a total market value of almost $78 billion. However, the Digital Analytics Association estimates that 44 percent of analytics teams spend more than half their time accessing and preparing data instead of analyzing data. That’s a dramatic investment for very little return.
 
According to Pyramid’s CEO Omri Kohl, there are five ways today’s analytics platforms are failing your data scientists:
 
The person who selected your analytics platform is not the person using it or benefiting from its insights.
 
Your analytics strategy only looks good on paper.
 
Data quality is a constant headache and your data scientists are spending more time cleansing data than analyzing it.
 
You’re so focused on optimizing your machine learning workflow that you’re missing the big picture.
 
The ad hoc nature of the business strains your advanced analytic users.
 
The recipe for success includes end-to-end analytics platforms that target the broadest set of users. This type of analytics environment that provides specific toolsets and functionality that are valuable to any participant in the decision lifecycle, end-users and data scientists alike. This increases value not only at the department level but across the enterprise.
 
Read Omri’s full article at Dataconomy here.